Human resource analytics with profile data

ABSTRACT

A method, computer program product, and system for human resource analytics using profile data is described. The method includes receiving historical project data, wherein the historical project data includes at least one profile of at least one historical project team member. Psychometric data associated with the at least one historical project team member is received. Updated historical project data is generated, in which, at least in part, psychometric data associated with the at least one historical project team member is added to the at least one profile included in the historical project data.

TECHNICAL FIELD

This disclosure relates to human resource analytics, and, moreparticularly, human resource analytics using profile data.

BACKGROUND

Organizations and individuals often assemble teams of one or moreindividuals in order to engage in and complete a specific project ortask. When assembling these teams, various parameters may be importantto the ultimate success of the project or task. For example, theexperience or educational qualifications of various team members may beimportant. Additionally hard constraints such as cost or completion datetargets may be important, as may be soft constraints such as theperceived opportunity to generate business from a customer beyond thecurrent project or task (i.e., cross-selling). Moreover, the social andprofessional dynamics of the interactions between team members may beimportant to the success of a project or task, from the perspective ofboth hard and soft constraints.

BRIEF SUMMARY OF THE DISCLOSURE

According to a first aspect of the disclosure, a method may includereceiving, via one or more computing devices, historical project data.The historical project data may include at least one profile of at leastone historical project team member. The method may further includereceiving, via the one or more computing devices, psychometric dataassociated with the at least one historical project team member. Themethod may also include generating, via the one or more computingdevices, updated historical project data including, at least in part,adding the psychometric data associated with the at least one historicalproject team member to the at least one profile included in thehistorical project data.

One or more of the following features may be included. The method mayinclude receiving at least one project requirement for a new project.The method may include determining a set of modified projectrequirements for the new project based upon, at least in part, comparingthe at least one project requirement for the new project with theupdated historical project data. The method may include creating atleast one data cluster including, at least in part, one or more portionsof at least one of the historical project data and the updatedhistorical project data. The psychometric data associated with the atleast one historical project team member may be, at least in part,determined from social networking sources. The psychometric dataassociated with the at least one historical project team member may be,at least in part, determined through sentiment analysis. The method mayinclude determining an optimal project team composition, based upon, atleast in part, the modified project requirements.

According to another aspect of the disclosure, a computer programproduct resides on a computer readable storage medium and has aplurality of instructions stored on it. When executed by a processor,the instructions cause the processor to perform operations includingreceiving historical project data. The historical project data includesat least one profile of at least one historical project team member. Theoperations include receiving psychometric data associated with the atleast one historical project team member. The operations further includegenerating updated historical project data including, at least in part,adding psychometric data associated with the at least one historicalproject team member to the at least one profile included in thehistorical project data.

One or more of the following features may be included. The operationsmay include receiving at least one project requirement for a newproject. The operations may include determining a set of modifiedproject requirements for the new project based upon, at least in part,comparing the at least one project requirement for the new project withthe updated historical project data. The operations may further includecreating at least one data cluster including, at least in part, one ormore portions of at least one of the historical project data and theupdated historical project data. The psychometric data associated withthe at least one historical project team member may be, at least inpart, determined from social networking sources. The psychometric dataassociated with the at least one historical project team member may be,at least in part, determined through sentiment analysis. The operationsmay include determining an optimal project team composition, based upon,at least in part, the modified project requirements.

According to another aspect of the disclosure, a computing systemincludes at least one processor and at least one memory architecturecoupled with the at least one processor. The computing system alsoincludes a first software module executable by the at least oneprocessor and the at least one memory architecture, wherein the firstsoftware module is configured to receive historical project data,wherein the historical project data includes at least one profile of atleast one historical project team member. Further, the computing systemincludes a second software module which may be configured to receivepsychometric data associated with the at least one historical projectteam member. The computing system also includes a third software modulewhich may be configured to generate updated historical project dataincluding, at least in part, adding psychometric data associated withthe at least one historical project team member to the at least oneprofile included in the historical project data.

One or more of the following features may be included. The computersystem may include a fourth software module executable by the at leastone processor and the at least one memory architecture, wherein thefourth software module may be configured to receive at least one projectrequirement for a new project. A fifth software module may be configuredto determine a set of modified project requirements for the new projectbased upon, at least in part, comparing the at least one projectrequirement for the new project with the updated historical projectdata. A sixth software module may be configured to create at least onedata cluster including, at least in part, one or more portions of atleast one of the historical project data or the updated historicalproject data. The psychometric data associated with the at least onehistorical project team member may be, at least in part, determined fromsocial networking sources. The psychometric data associated with the atleast one historical project team member may be, at least in part,determined through sentiment analysis.

According to another aspect of the disclosure, a method includesdetermining, via one or more computing devices, a set of modifiedproject requirements for a new project based upon, at least in part,comparing at least one project requirement for the new project withupdated historical project data. The updated historical project dataincludes, at least in part, psychometric data associated with at leastone historical project team member.

One or more of the following features may be included. The updatedhistorical project data may include at least one data cluster. Thepsychometric data associated with at least one historical project teammember may be, at least in part, determined from social networkingsources. The psychometric data associated with the at least onehistorical project team member may be, at least in part, determinedthrough sentiment analysis.

According to another aspect of the disclosure, a computer programproduct resides on a computer readable storage medium and has aplurality of instructions stored on it. When executed by a processor,the instructions cause the processor to perform operations includingdetermining a set of modified project requirements for a new projectbased upon, at least in part, comparing at least one project requirementfor the new project with updated historical project data. The updatedhistorical project data includes, at least in part, psychometric dataassociated with at least one historical project team member.

One or more of the following features may be included. The updatedhistorical project data may include at least one data cluster. Thepsychometric data associated with at least one historical project teammember may be, at least in part, determined from social networkingsources. The psychometric data associated with the at least onehistorical project team member may be, at least in part, determinedthrough sentiment analysis.

The details of one or more implementations are set forth in theaccompanying drawings and the description below. Other features andadvantages will become apparent from the description, the drawings, andthe claims.

BRIEF DESCRIPTION OF THE SEVERAL VIEWS OF THE DRAWINGS

FIG. 1 is a diagrammatic view of a human resource analytic processcoupled to a distributed computing network;

FIG. 2 is a flowchart view of a human resource analytic process;

FIG. 3 is a diagrammatic view of a human resource analytic process;

FIG. 4 is a diagrammatic view of a portion of a human resource analyticprocess; and

FIG. 5 is a diagrammatic view of a portion of a human resource analyticprocess.

Like reference symbols in the various drawings indicate like elements

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

Referring to FIGS. 1 & 2, there is shown a human resource analytic (HRA)process, for example process 12. As will be discussed further below,process 12 may include receiving 100 historical project data. Process 12may also include receiving 102 psychometric data. Process 12 may alsoinclude generating 104 updated historical project data. Further, process12 may include receiving at least one project requirement 118.Additionally, process 12 may include determining 114 a set of modifiedproject requirements, including comparing 112 the updated historicalproject data and the new project requirement. Process 12 may alsoinclude determining 116 an optimal team composition.

A HRA process may be a server-side process (e.g., server-side process10), a client-side process (e.g., client-side process 12, client-sideprocess 14, client-side process 16, or client-side process 18), or ahybrid server-side/client-side process (e.g., the combination ofserver-side process 10 and one or more of client-side processes 12, 14,16, 18).

Server-side process 10 may reside on and may be executed by servercomputer 20, which may be connected to network 22 (e.g., the Internet ora local area network). Examples of server computer 20 may include, butare not limited to: a personal computer, a server computer, a series ofserver computers, a mini computer, and/or a mainframe computer. Servercomputer 20 may be a web server (or a series of servers) running anetwork operating system, examples of which may include but are notlimited to: Microsoft® Windows Server®; Novell® Netware®; or Red Hat®Linux®, for example.

The instruction sets and subroutines of server-side process 10, whichmay be stored on storage device 24 coupled to server computer 20, may beexecuted by one or more processors (not shown) and one or more memoryarchitectures (not shown) incorporated into server computer 20. Storagedevice 24 may include but is not limited to: a hard disk drive; a tapedrive; an optical drive; a RAID array; a random access memory (RAM); anda read-only memory (ROM).

Server computer 20 may execute a web server application, examples ofwhich may include but are not limited to: Microsoft® IIS, Novell® WebServer, or Apache® Web Server, that allows for access to server computer20 (via network 22) using one or more protocols, examples of which mayinclude but are not limited to HTTP (i.e., HyperText Transfer Protocol),SIP (i.e., session initiation protocol), and the Lotus®Sametime® VPprotocol. Network 22 may be connected to one or more secondary networks(e.g., network 26), examples of which may include but are not limitedto: a local area network; a wide area network; or an intranet, forexample.

Client-side processes 12, 14, 16, 18 may reside on and may be executedby client electronic devices 28, 30, 32, and/or 34 (respectively),examples of which may include but are not limited to personal computer28, laptop computer 30, a data-enabled mobile telephone 32, notebookcomputer 34, personal digital assistant (not shown), smart phone (notshown) and a dedicated network device (not shown), for example. Clientelectronic devices 28, 30, 32, 34 may each be coupled to network 22and/or network 26 and may each execute an operating system, examples ofwhich may include but are not limited to Microsoft® Windows®, MicrosoftWindows CE®, Red Hat® Linux®, or a custom operating system.

The instruction sets and subroutines of client-side processes 12, 14,16, 18, which may be stored on storage devices 36, 38, 40, 42(respectively) coupled to client electronic devices 28, 30, 32, 34(respectively), may be executed by one or more processors (not shown)and one or more memory architectures (not shown) incorporated intoclient electronic devices 28, 30, 32, 34 (respectively). Storage devices36, 38, 40, 42 may include but are not limited to: hard disk drives;tape drives; optical drives; RAID arrays; random access memories (RAM);read-only memories (ROM); compact flash (CF) storage devices; securedigital (SD) storage devices; and memory stick storage devices.

One or more of client-side processes 12, 14, 16, 18 and server-sideprocess 10 may interface with each other (via network 22 and/or network26).

Users 44, 46, 48, 50 may access server-side process 10 directly throughthe device on which the client-side process (e.g., client-side processes12, 14, 16, 18) is executed, namely client electronic devices 28, 30,32, 34, for example. Users 44, 46, 48, 50 may access server-side process10 directly through network 22 and/or through secondary network 26.Further, server computer 20 (i.e., the computer that executesserver-side process 10) may be connected to network 22 through secondarynetwork 26, as illustrated with phantom link line 52.

The various client electronic devices may be directly or indirectlycoupled to network 22 (or network 26). For example, personal computer 28is shown directly coupled to network 22 via a hardwired networkconnection. Further, notebook computer 34 is shown directly coupled tonetwork 26 via a hardwired network connection. Laptop computer 30 isshown wirelessly coupled to network 22 via wireless communicationchannel 54 established between laptop computer 30 and wireless accesspoint (i.e., WAP) 56, which is shown directly coupled to network 22. WAP56 may be, for example, an IEEE 802.11a, 802.11b, 802.11g, 802.11n,Wi-Fi, and/or Bluetooth device that is capable of establishing wirelesscommunication channel 54 between laptop computer 30 and WAP 56.Data-enabled mobile telephone 32 is shown wirelessly coupled to network22 via wireless communication channel 58 established betweendata-enabled mobile telephone 32 and cellular network/bridge 60, whichis shown directly coupled to network 22.

As is known in the art, all of the IEEE 802.11x specifications may useEthernet protocol and carrier sense multiple access with collisionavoidance (i.e., CSMA/CA) for path sharing. The various 802.11xspecifications may use phase-shift keying (i.e., PSK) modulation orcomplementary code keying (i.e., CCK) modulation, for example. As isknown in the art, Bluetooth is a telecommunications industryspecification that allows e.g., mobile phones, computers, and personaldigital assistants to be interconnected using a short-range wirelessconnection.

A Human Resource Analytic (HRA) Process

Often when an individual or organization undertakes a new project,various parameters may constrain the composition of the team or teamsthat will be assigned to the new project. These parameters may relate tovarious aspects of a project, including, for example, cost and datecompletion targets and constraints on the desired optimal teamcomposition, and may include, for example, both hard parameters and softparameters.

Hard parameters may include, for example, project timelines, the targetcompletion date or the target completion cost. Hard parameters may alsoinclude, for example, the particular outcome desired for a project(e.g., the specific accomplishments or finished products that willindicate successful completion the project). Additionally, hardparameters may include restrictions on the members that will comprisethe team. For example, for a particular project hard constraints mayinclude the requirement that a team member have a particular educationaldegree (e.g., a Ph.D. in nuclear engineering), a particularcertification (e.g., a professional engineer's certificate), or aparticular licensure (e.g., admission as an attorney to the bar of aparticular state). Other example of hard parameter restrictions on teammembers may include, but are not limited to, geographical location(e.g., only team members located in Malaysia), or years of experience(e.g., at least one team member must have 30 years of experience at thecompany or 15 years of experience with a particular type of project).Hard parameter restrictions on team members may relate to particularteam members (as in some of the examples above) or may relate to aportion of a team including multiple team members, or may relate to ateam as a whole: for example, one hard constraint might require that thesum of personal experience with a typical project exceed a certainnumber of years (e.g., a team is required to have, in total, 50 years ofexperience laying under-sea cable, although no individual team member isrequired to have that many years of experience individually).

Soft parameters, like hard parameters, may relate to particular aspectsof a project or to a project as a whole. For example, soft parametersmay include factors relating to client satisfaction with the project orto development of additional business, such as the perceived opportunityto cross-sell additional products or services to the client for whom aproject is being undertaken. Additionally, soft parameters may relatespecifically to individual team members, to groups of team members. Forexample, soft parameters might relate to the personality of a teammember, to a team member's business acumen or ability to developbusiness beyond a currently assigned project, or to a team member'sability to work with and/or direct other team members. One specificexample of soft parameters includes data that may be gleaned frompsychometric data.

Psychometric data may relate to mental abilities and psychologicalcharacteristics and may result from psychometric analysis (sometimesalso referred to as psychological or occupational analysis or testing).In some instances, psychometric analysis may be designed to test anindividual's mental abilities and psychological characteristics in acontrolled setting and on a scientifically quantifiable basis. It may bebased on statistical studies or other bodies of evidence and may addressdiverse areas of psychological characteristics and mental abilities,including general intelligence, social intelligence, and personalitytraits.

Psychometric analysis tests and procedures may be accredited byprofessional psychological organizations or by other bodies and areoften designed to assist businesses with recruiting and general humanresource analysis. Psychometric data may include various types of datafrom psychometric analysis, including, but not limited to, for example,data relating to a personality type or personality trait of anindividual. Psychometric data may also include, but is not limited to,information relating to the social, intellectual or professionalinclinations or tendencies of an individual.

One common type of psychometric test is the Myers-Briggs Type Indicatorpersonality inventory (MBTI), which is based on the identification of 16distinctive personality types. Using questions relating to preferences(e.g., “Do you usually prefer A or B?”) the MBTI analysis may categorizeindividuals as belonging to one category from each of the followingpairs: Extraverted (“E”) or Introverted (“I”); Sensing (“S”) orIntuitive (“N”); Thinking (“T”) or Feeling (“F”); Judging (“J”) orPerceiving (“P”). Accordingly, any given individual completing an MBTIevaluation may be categorized according to one of the 16 possiblecombinations of the elements of these pairs. For example, one individualmay be classified as INTP (Introverted, Intuitive, Thinking, Perceiving)which may indicate, respectively, a general preference to focus on theinner world, to add interpretation or meaning to basic information shereceives, to make decisions based on logic and consistency, and toremain open to new information and options. Another individual, forexample, may be classified as ESFJ (Extroverted, Sensing, Feeling,Judging), which may indicate, respectively, a general preference tofocus on the outer world, to focus on basic information without addinginterpretation or meaning, to consider people and other specialcircumstances before making decisions, and to make final decisionsrelating to the outside world rather than staying open to newinformation and options. MBTI analysis may not be a ranking analysis(e.g., no categorization is a “better” or “preferable” categorization),but rather may be intended to aid in the understanding of individuals'preferences when they are confronted with questions, tasks, problems,and other scenarios.

Another type of psychometric test is the Hermann Brain DominanceInstrument (HBDI) analysis. The HBDI model may divide thinking into fourdifferent modes: analytical thinking (e.g., collecting data, logicalreasoning, etc.); sequential thinking (e.g., following directions,organization, etc.); interpersonal thinking (e.g., listening to andexpressing ideas, group interaction, etc.); and imaginative thinking(e.g., taking initiative, creative problem solving, etc.). HBDI testingmay aim to identify personal preferences or inclinations toward aparticular mode of thinking, often in order to determine a dominantpreference as well as a generalized ranking (e.g., one individual'sthinking may be dominantly interpersonal, with some inclination towardsequential and imaginative thinking, and weaker inclination towardanalytical thinking).

Another type of psychometric test is the Profile XT assessment. This maybe an assessment of job-related qualities including thinking andreasoning style, behavioral traits, and occupational interests. ProfileXT assessment may sometimes be described as “total person concept”analysis and may include assessment of verbal and numerical reasoning,behavioral traits and work interests, as well as job-fit analysis thatmay be intended to match a particular individual with a particular jobor task.

Another type of psychometric test is the Thomas Personal ProfileAnalysis (Thomas PPA). Like the HBDI model, Thomas PPA may endeavor toassess individuals based on four characteristics, although thecharacteristics used by Thomas PPA (e.g., dominance, inducement,submission and compliance) may differ from those used in the HBDI model.Thomas PPA may recognize that different individuals may express each ofthese characteristics more or less strongly at any particular time, andthat individuals may tend, generally, to more strongly display certainof these characteristics than others. Thomas PPA tests may utilizetetrads of descriptive words, from which test takers are prompted tochose the word which they feel best describes their personality. Theanswers may then be analyzed to determine which of the four Thomas PPAcharacteristics a particular individual may most strongly exhibit.

The psychometric tests described above (e.g., HBDI, Profile XT, MBTI,Thomas PPA) and other psychometric tests are sometimes referred to as“individual” profile tests, because they are typically completed by anindividual herself. “Individual” profile tests may often not provide acomplete picture of an individual's true psychometric profile (e.g., maynot result in complete or completely accurate psychometric data). Thismay be because, for example, individuals may fail to assess their ownpersonality with objectivity and honesty. Self-analysis may be difficultfor some individuals, which may be further compounded by the anxiety ofbeing “tested” or “analyzed.” Further, when psychometric tests areadministered in an employment context, individuals may adjust(consciously or sub-consciously) their answers in order to more closelyapproximate what they believe may be the “right” answer, from theperspective of the test administrator. In many psychometric tests thisfocus on the “right” answer may skew the results away from accuracy.

Accordingly, it may sometimes be useful to employ tests that arepartially or entirely feedback-based. “Feedback-based” profiling, mayavoid the potential self-assessment bias of “individual” profile test.“Feedback-based” types of test may utilize input from individuals otherthan the individual being analyzed in order to construct a more accurateand complete psychometric profile (e.g., to determine a more completeand accurate set of psychometric data). For example, Belbin 360 analysismay be used to create a Belbin Self-Perception Profile (SPI) through thecombination of self-reporting and observer assessments. The observerassessment process may include soliciting managers, colleagues andsubordinates of an individual to complete a short assessment of thatindividual, which may include various types of psychometric data.

Although various types of psychometric analysis tests have beendescribed above, it will be understood that psychometric analysis mayinclude the collection of psychometric data through types of analysisnot included in the lists above. The analysis may sometimes beadministered by certified or trained professionals or by non-expertpersons, or may sometimes be self-administered through a variety ofmeans, including administration over the world wide web or through othermedia. Psychometric analysis may focus on purely psychological traits,as in, for example, MBTI analysis, on behavioral traits, as in, forexample, Belbin SPI, or a combination of the two.

For the following discussion, client-side HRA process 12 will bedescribed for illustrative purposes. It should be noted that client-sideprocess 12 may be incorporated into server-side process 10 and may beexecuted within one or more applications that allow for communicationwith client-side process 12. However, this is not intended to be alimitation of this disclosure, as other configurations are possible(e.g., stand-alone client-side processes and/or stand-alone server-sideprocesses.) For example, some implementations may include one or more ofclient-side processes 14, 16, 18 in place of or in addition toclient-side process 12.

Process 12 may include receiving 100, via one or more computing devices,historical project data. Often an organization or an individual willretain data relating to projects that have been undertaken in the past.For example, an organization may retain information regarding projecthard parameters (e.g., team composition, project timelines, the targetand actual completion dates or the target and actual completion cost ofthe project), and project soft parameters (e.g., whether cross-sellingopportunities were realized or whether the client was satisfied). Thishistorical project data may be stored in a variety of ways, including,for example, referring now to FIG. 3, in database 202, which may bestored, for example, on storage device 36 or on another storage device(e.g., storage device 24). The historical project data may include atleast at least one profile of at least one historical project teammember. For example, if Project X was undertaken by a team consisting ofhistorical project team members Adams, Bates, Charles, and Danbury,profile information related to at least one of those four team membersmay be included in the historical project data. For example, thehistorical project data may include a list a of the four team members aswell as the profile information that Adams has a Master's Degree inComputer Science, that Bates has 6 years of experience in the company,and that Charles has worked on 12 successful software architectureprojects. Profile information may further include, for example, variousother human resources information, including, but not limited to, age,position in the company, salary, and employment and educational history.

Process 12 may further include receiving, via the one or more computingdevices, psychometric data associated with the at least one historicalproject team member. For example, if MBTI-type data were used by theorganization, process 12 may include receiving the information thatAdams has been classified as an INTP personality type, while Charles hasbeen classified as an ESFJ personality type. This information may bedirectly relevant to various aspects of a historical (or future)project. For example, considering again MBTI-type psychometric data, itmay be found that various project parameters may be satisfied or notsatisfied depending on the psychometric profiles or combination ofpsychometric profiles present on a given team. For example, a team withno individual exhibiting an Extroverted-type personality may be found torarely complete successful cross-selling of additional products orservices because no team member is particularly comfortable engaging insales activity. Or a team with no Feeling-type personality may be foundto exhibit poor team dynamics due to the absence of an individual whocan skillfully balance complicated inter-personal relationship factors.Further, particular combinations of MBTI-type (or types based otherpsychometric analyses) may be found to result in favorable hardparameter results—e.g., on-time and under-budget completion ofparticular types of projects—while other combinations may result in lessfavorable outcomes.

Psychometric data may be received from a variety of sources. Forexample, an organization may maintain database 200 of availableresources (e.g., individuals or teams of individuals), which may includeprofiles of individuals who have worked on historical projects as wellas profiles of individuals who have not participated in historicalprojects but are currently available to participate new projects. Theprofiles included in database 200 may include psychometric dataassociated with the these individuals, including psychometric dataassociated with the individuals who have worked on historical projectsas well as psychometric data associated with individuals who areavailable for future projects but may not have worked on a historicalproject. It will be understood that database 200 may be stored, forexample, on storage device 36 or on another storage device (e.g.,storage device 24).

Process 12 may further include generating 104, via the one or morecomputing devices, updated historical project data. Generating updatedhistorical project data may include, for example, adding thepsychometric data associated with one or more historical project teammember (e.g., psychometric data stored in the profiles of database 200)to the one or more profiles included in the historical project data. Forexample, an organization may maintain database 200 of availableresources and database 202 of historical project data, in which casegenerating 104 updated historical project data may include receivingpsychometric data from database 200 and supplementing the profiles ofteam members in the database 202 with that psychometric data.Psychometric data from one individual's profile included in, forexample, database 200 may be added to the same individual's profileincluded in, for example, database 202.

As a further example, referring now also to FIG. 4, profiles 302 of oneor more historical team members (e.g., the profiles of Adams andCharles), which may be stored in database 200, may include various typesof psychometric data. For example, profiles 302 may include results fromsources including, but not limited to, individual profile tests 304(e.g., MBTI test results), feedback based tests 306 (e.g., Belkin 360analysis results), and psychometric data determined from social networksources 308. Historical project data, which may be stored in database202, may include hard and soft parameters relating to a particularproject (e.g., Project X) including profiles of one or more of the samehistorical team members (e.g., the profiles of Adams and Charles). Theseprofiles, because they are part of the historical project data that hasnot yet been updated, may include various types of profile information(e.g., years of experience, qualifications, job title, etc.) but may notinclude psychometric data. Updated historical project data, which may bestored in database 204, may include these same profiles of historicalteam members, as well as psychometric data (e.g., psychometric data fromprofiles 302) in addition to hard and soft parameters associated withvarious historical projects. It will be understood that variousdatabases in the FIGS. 3-5 (e.g., database 204 and database 202) may bestored in the same storage device (e.g., storage device 36), or on twoor more separate storage devices (e.g., storage devices 36 and 24).

Process 12 may further include receiving new project requirements 118.As an example, new project requirements 118 may include one or more hardparameters for a new project such as target completion data, targetbudget, and necessary professional or experience qualifications for oneor more team members. New project requirements 118 may also include, forexample, one or more soft parameters for a new project, such as whetherthere may exist opportunities to cross-sell or otherwise derive futurebusiness from the client associated with the new project. For example,new Project Y may include new project requirements 118 including, butnot limited to, a team including at least two individuals with Ph.D.s inastrophysics, a target completion date of Mar. 31, 2015, a target budgetof $12.3 Million, that the client may be amenable to cross-selling, andthat the finished product must be aesthetically pleasing.

Process 12 may further include determining 114 a set of modified projectrequirements 208 for the new project. Determining 114 set of modifiedproject requirements 208 may be based upon, at least in part, comparing112 new project requirements 118 with the updated historical projectdata of database 204. For example, new project requirements 118 mayinclude various hard and soft parameters that are similar to the hardand soft parameters of one or more projects included in the updatedhistorical project data. Comparison of new project requirements 118 withthe updated historical project data may reveal these similarities.Further, the updated historical project data may include the success ofa historical project (e.g., whether the project was complete on time andunder budget, and whether, for example, cross-selling opportunities wererealized) as well as psychometric data relating to various historicalproject team members. Accordingly, modified project requirements 208 maybe determined, based, for example, upon the comparison of new projectrequirements 118 and the updated historical project data, to include theoriginal hard and soft parameters of new project requirements 118 aswell as a desired team composition based on psychometric data includedin the updated historical project data. New project requirements 118 maybe expressed as a vector including this information, for easy operationwithin a computational architecture.

As an example, data related to historical Project X may be included inthe updated historical project data and may include various hard andsoft parameters including, but not limited to a team including at leasttwo individuals with Ph.D.s in chemistry, a target completion date ofDec. 1, 2004, a target budget of $26 Million, that the client may beamenable to cross-selling, and that the finished product must beaesthetically pleasing. Further, the updated historical project datarelated to historical Project X may include the information that theteam contained two Ph.D.s with MBTI type ENFJ personalities and thatProject X was completed on time, under budget, with an aestheticallypleasing result and with successful cross-selling. Comparing 112 the newproject requirements 118 of Project Y with the updated historicalproject data may reveal that Project X and Project Y both included thehard and soft parameters of a team including at least two individualswith Ph.D.s in a technical field, a target budget of several milliondollars, the requirement of aesthetically pleasing results, and theopportunity to cross-sell. Further, a second historical project, ProjectZ, may include similar hard and soft parameters, but instead include ateam with two individuals with Ph.D.s in a technical field having MBTItype INFJ personalities. Project Z, for example, may have been completedon time and under budget, but without an aesthetically pleasing resultand without successful cross-selling. Accordingly, modified projectrequirements 208 associated with new Project Y may include a preferenceto include two individuals with Ph.D.s with MBTI type ENFJpersonalities, and a preference not to include two individuals withPh.D.s with MBTI type INFJ personalities.

As a further example, if a certain type historical project with similarhard and soft parameters to those included in new project requirements118 is found to have been most successful when the historical projectteam included at least one team member of MBTI type ISFP (Introverted,Sensing, Feeling, Perceiving) and at least one team member of MBTI typeENFP (Extroverted, Intuitive, Feeling, Perceiving), modified projectrequirement 208 may include a preference for a team including at leastone team member of MBTI type ENFP and ISFP. Similarly, if the same typeof historical project is found to have been less successful when thehistorical project team included more than two team members of MBTI typeEITJ (Extroverted, Intuitive, Thinking, Judging), modified projectrequirement 208 may include a preference for a team not including morethan two team members of MBTI type EITJ.

Process 12 may further include creating 106 at least one data clusterincluding, at least in part, one or more portions of at least one of thehistorical project data and the updated historical project data. Thetechnique of creating data clusters is well known in the art and maygenerally include assigning portions of data within a larger set intosubsets (“clusters”) based on certain similarities between the elementsof each particular subset. Creating 106 at least one data cluster mayresult in comparing 112 new project requirements 118 with historicalproject data proceeding more simply or with greater speed, as it may notbe necessary to compare 112 new project requirements 118 with everyhistorical project, but only with the cluster or clusters of historicalprojects that most closely resemble new project requirements 118. Itwill be understood that a variety of factors may be employed in order todetermine the content of clusters. For example, one cluster of updatedhistorical project data may include projects requiring a team consistingonly of highly educated technical workers. As another example, anothercluster of updated historical project data may include projectsrequiring capital expenditure of more than $100 Million.

Creating 106 at least one data cluster may be performed with respect tohistorical project data, updated historical project data, or both, andmay be achieved through the use of various artificial intelligencetechniques, as well as, for example, through an expert system approach.An expert system approach may generally includes the use of a knowledgebase of human expertise for software-implemented problem solving,sometimes including a series of if-then analysis statements, rooted inhuman-developed expertise, and often coupled with certainty parameters(e.g., if a project included a drilling expert, then it relates tosubterranean operations (certainty 75%)).

The psychometric data associated with historical project members, e.g.,the psychometric data included in historical team member profiles 302,may also include psychometric data that has been determined from socialnetworking sources.

Social networking sources (sometimes also referred to as “social media”sources or “Web 2.0” sources) include a variety of sources, which aregenerally characterized by the ability of individuals or groups toparticipate socially in a network-based forum. In some instances, socialnetworking sources may be the primary focus of a product or application.For example, the social networking website www.facebook.com allows usersto create personal profiles, to select groups of individuals with whichto more closely associate themselves, and to share comments, status,location, thoughts, photos, videos, website links and a variety of othercontent in a personalized manner. As another example, the websitewww.linkedin.com allows users to create a personal profile in order toconnect to and interact with various professional contacts and networks,often with the purpose of exploring career opportunities or developingbusiness contacts.

As a further example, individuals often create online records of theiractivities, thoughts or interests, or of particular subject matter thatis of interest to them (these online records are sometimes referred toas web-logs or “blogs”). Through blogs, individuals (known as“bloggers”) can share original, derived or otherwise obtained content.This sharing may include any individual with a standard internetconnection (e.g., open blogs) or may include only a specified group ofindividuals (e.g., blogs with restricted membership or restrictedaccess).

In other instances, social networks may operate as a peripheral orsecondary function of a product or application. For example, manywebsites devoted to providing news or entertainment content may allowtheir users to comment or otherwise respond to various news stories orother content. Often the overall length of the comment sections of thesewebsites may exceed the overall length of the original website content,indicating a rich and extensive social interaction among participants.Similarly, retail sites may allow users to post reviews and other usefulinformation on product webpages.

Additionally, certain platforms may provide for social interaction amongusers divorced from any formalized content. For example, the serviceTwitter allows users to update a feed of comments from a variety ofsources (e.g., from mobile telephones) while simultaneously deliveringthe feed to any other user who requests it. In this way, as with certainother types of social media, information may be shared by a single userwith a multitude of others. By contrast, certain social networkingplatforms may provide for online social interaction but in a moreprescribed manner and only with a select group of individuals (e.g.,instant messaging services, in which users can communicate in areal-time manner over a network, but only with a selected group ofindividuals).

The examples above are merely a sample of many different types of socialnetworking sources. Further, although these examples are discussed in anisolated context, it will be understood that various types of socialnetworking sources may sometimes be combined. For example, it may bepossible for a news-content website to allow automated connection ofparticular story with a user's Facebook page (e.g., through the use of a“Like” button). As another example, a Twitter user may includeinformation linking to text, video, audio or other content in itssubmissions to the Twitter service, which other Twitter users may thenview and respond to. As another example, within a particular blog ablogger may link to or embed content relating to, for example, anentertainment story, while simultaneously allowing the readers of theblog to comment and discuss the content within the confines of the blog.

Social networking sources may provide a rich trove of psychometricinformation. For example, the mere presence of an individual on avariety of social networking media may indicate, using MBTI categoriesas an example, that the person exhibits Extroversion and Feelingtendencies. As another example, an individual who maintains one or moreblogs dedicated to a particular technology or comments exclusively ontechnology-related media may be determined to exhibit a particularlyanalytical personality type. As a further example, an individual whocomments on a variety of topics with great frequency may be determinedto exhibit a more critical personality type. Accordingly, for example,psychometric data included in historical team member profiles 302 mayinclude psychometric data 308 determined from social networking sources,e.g., social networking data 108.

In addition to and, sometimes, in combination with the determination ofpsychometric data from social networking sources, process 12 may furtherinclude determining psychometric data through sentiment analysis 110.Sentiment analysis relates generally to the analysis of spoken orwritten statements in order to identify and extract informationregarding the author of the statements. For example, one aspect ofsentiment analysis may include classifying the polarity of a phrase(e.g., a phrase from an online comment, a blog entry, or another socialnetworking source), which may indicate whether the phrase expresses apositive, negative or neutral sentiment. For example, a comment that isdeeply critical of a news report or that used offensive language towarda previous commenter may be classified as negative, a message via aninstant messaging service or Twitter that employs supportive language(e.g., “way to go!” or “this is great!”) may be classified as positive,and a blog post regarding the optimal conditions for rainfall in theAmazon may be classified as neutral.

Psychometric data derived from sentiment analysis (e.g., sentimentanalysis 110) and included in updated historical project data (e.g.,database 204) or available resources (e.g., database 200) may be usefulto determining modified project requirements. For example, thepsychometric data included in historical team member profiles 302, mayinclude psychometric data determined from sentiment analysis. Thissentiment analysis may indicate, for example, that a particularhistorical team member frequently comments on news stories, blogs orother social networking sources in ways that could be characterized asnegative, which may suggest that this particular team member has ananalytical perspective. Accordingly, this particular team member may bewell suited for quantitative analysis. This sentiment analysis may alsosuggest, however, that this team member may not be sufficientlysupportive of alternative viewpoints to act as a manager of a large ordiverse team. Alternatively, sentiment analysis may indicate that a teammember is almost universally positive in her participation in socialnetwork forums and therefore may be a strong leader of a diverse team.

Referring now also to FIG. 5, process 12 may further include determining116 an optimal project team composition 210, based upon, at least inpart, modified project requirements 208. For example, process 12 mayinclude an objective function f, as is well known in the art, theparameters of which include hard and soft parameters relating toavailable resources (e.g., those included in database 200) as well ashard and soft parameters relating to modified project requirements 208.Hard parameters relating to available resources may include, forexample, the professional or academic qualifications or the geographicallocation of individuals available to participate in future projects.Hard parameters relating to modified project requirements 208 mayinclude, for example, the necessary professional or academicqualifications of the geographical location of individuals necessary fora new project. Soft parameters relating to available resources (e.g.,those included in database 200) may include psychometric data associatedwith individuals available to participate in future projects. Softparameters relating to modified project requirements 208 may includepsychometric data associated with the desired team composition for a newproject, which may be determined, for example, by comparing 112 newproject requirements 118 with updated historical project data included,for example, in database 204.

The objective function f may include determining a difference betweenthe hard parameters relating to the available resources and the hardparameters relating to the modified project requirements as well as thedifference between the soft parameters relating to the availableresources and the soft parameters relating to the modified projectrequirements. The objective function may further include, for example, aweighting factor K, which may increase or decrease the importance of thesoft parameters. The objective function may be minimized by variousmethods, as is well known in the art, in order to determine 116 anoptimal project team composition 210. Optimal project team composition210 may include a single optimal team composition or may include aranked or unranked list of various desired or undesired teamcompositions, as may be useful if not all individuals included asavailable resources will be able to participate in every project forwhich they are recommended.

It will be understood that process 12 may, in certain embodiments, beimplemented through the use of human assistance. For example, in thecase that the updated historical project data (e.g., database 204) isnot rich enough (e.g., does not contain enough projects or projectclusters to perform meaningful comparison of the updated historicalproject data with new project requirements 118) a human expert 206 mayassist in determining modified project requirements 208. For example,human expert 206 may recognize that a particular new project will needan individual with a particular MBTI profile (e.g., INFP—Introverted,Intuitive, Feeling, Perceiving). However, it may also be true that nohistorical project included such a team member, and, accordingly, theupdated historical project data does not include information relating tosuch an INFP resource. Accordingly, human expert 206 may supplementmodified project requirements 208 with the additional projectrequirement of including an INFP resource on the project team.

As will be appreciated by one skilled in the art, aspects of the presentinvention may be embodied as a system, apparatus, method or computerprogram product. Accordingly, aspects of the present invention may takethe form of an entirely hardware embodiment, an entirely softwareembodiment (including firmware, resident software, micro-code, etc.) oran embodiment combining software and hardware aspects that may allgenerally be referred to herein as a “circuit,” “module” or “system.”Furthermore, aspects of the present invention may take the form of acomputer program product embodied in one or more computer readablemedium(s) having computer readable program code embodied thereon.

Any combination of one or more computer readable medium(s) may beutilized. The computer readable medium may be a computer readable signalmedium or a computer readable storage medium. A computer readablestorage medium may be, for example, but is not limited to, anelectronic, magnetic, optical, electromagnetic, infrared, orsemiconductor system, apparatus, or device, or any suitable combinationof the foregoing. More specific examples (a non-exhaustive list) of thecomputer readable storage medium may include the following: anelectrical connection having one or more wires, a portable computerdiskette, a hard disk, a random access memory (RAM), a read-only memory(ROM), an erasable programmable read-only memory (EPROM or Flashmemory), an optical fiber, a portable compact disc read-only memory(CD-ROM), an optical storage device, a magnetic storage device, or anysuitable combination of the foregoing. In the context of this document,a computer readable storage medium may be any tangible medium that cancontain, or store a program for use by or in connection with aninstruction execution system, apparatus, or device.

A computer readable signal medium may include a propagated data signalwith computer readable program code embodied therein, for example, inbaseband or as part of a carrier wave. Such a propagated signal may takeany of a variety of forms, including, but not limited to,electro-magnetic, optical, or any suitable combination thereof. Acomputer readable signal medium may be any computer readable medium thatis not a computer readable storage medium and that can communicate,propagate, or transport a program for use by or in connection with aninstruction execution system, apparatus, or device.

Program code embodied on a computer readable medium may be transmittedusing any appropriate medium, including but not limited to wireless,wireline, optical fiber cable, RF, etc., or any suitable combination ofthe foregoing.

Computer program code for carrying out operations for aspects of thepresent invention may be written in any combination of one or moreprogramming languages, including an object oriented programming languagesuch as Java, Smalltalk, C++ or the like and conventional proceduralprogramming languages, such as the “C” programming language or similarprogramming languages. The program code may execute entirely on theuser's computer (i.e., a client electronic device), partly on the user'scomputer, as a stand-alone software package, partly on the user'scomputer and partly on a remote computer or entirely on the remotecomputer or server (i.e., a server computer). In the latter scenario,the remote computer may be connected to the user's computer through anytype of network, including a local area network (LAN) or a wide areanetwork (WAN), or the connection may be made to an external computer(for example, through the Internet using an Internet Service Provider).

Aspects of the present invention may be described with reference toflowchart illustrations and/or block diagrams of methods, apparatus(systems) and/or computer program products according to embodiments ofthe invention. It will be understood that each block of the flowchartillustrations and/or block diagrams, and combinations of blocks in theflowchart illustrations and/or block diagrams, can be implemented bycomputer program instructions. These computer program instructions maybe provided to a processor of a general purpose computer, specialpurpose computer, or other programmable data processing apparatus toproduce a machine, such that the instructions, which execute via theprocessor of the computer or other programmable data processingapparatus, create means for implementing the functions/acts specified inthe flowchart and/or block diagram block or blocks.

These computer program instructions may also be stored in a computerreadable medium that can direct a computer, other programmable dataprocessing apparatus, or other devices to function in a particularmanner, such that the instructions stored in the computer readablemedium produce an article of manufacture including instructions whichimplement the function/act specified in the flowchart and/or blockdiagram block or blocks.

The computer program instructions may also be loaded onto a computer,other programmable data processing apparatus, or other devices to causea series of operational steps to be performed on the computer, otherprogrammable apparatus or other devices to produce a computerimplemented process such that the instructions which execute on thecomputer or other programmable apparatus provide processes forimplementing the functions/acts specified in the flowchart and/or blockdiagram block or blocks.

The flowchart and block diagrams in the figures may illustrate thearchitecture, functionality, and operation of possible implementationsof systems, methods and computer program products according to variousembodiments of the present invention. In this regard, each block in theflowchart or block diagrams may represent a module, segment, or portionof code, which comprises one or more executable instructions forimplementing the specified logical function(s). It should also be notedthat, in some alternative implementations, the functions noted in theblock may occur out of the order noted in the figures. For example, twoblocks shown in succession may, in fact, be executed substantiallyconcurrently, or the blocks may sometimes be executed in the reverseorder, depending upon the functionality involved. Further, one or moreblocks shown in the block diagrams and/or flowchart illustration may notbe performed in some implementations or may not be required in someimplementations. It will also be noted that each block of the blockdiagrams and/or flowchart illustration, and combinations of blocks inthe block diagrams and/or flowchart illustration, can be implemented byspecial purpose hardware-based systems that perform the specifiedfunctions or acts, or combinations of special purpose hardware andcomputer instructions.

A number of embodiments and implementations have been described.Nevertheless, it will be understood that various modifications may bemade. Accordingly, other embodiments and implementations are within thescope of the following claims.

1-6. (canceled)
 7. A computer program product residing on a computerreadable storage medium having a plurality of instructions storedthereon, which, when executed by a processor, cause the processor toperform operations comprising: receiving historical project data,wherein the historical project data includes at least one profile of atleast one historical project team member, one or more historical projectrequirements, and one or more historical project results; receivingpsychometric data associated with the at least one historical projectteam member; generating updated historical project data including, atleast in part, adding psychometric data associated with the at least onehistorical project team member to the at least one profile included inthe historical project data; receiving one or more new projectrequirements associated with a new project identifying a similaritybetween the one or more historical project requirements and the one ormore new project requirements; identifying an indication of successassociated with the psychometric data included in the updated historicalproject data and with the one or more historical project requirementsidentified as similar to the one or more new project requirements; anddetermining a set of modified project requirements for the new projectbased upon, at least in part, identifying the indication of success. 8.(canceled)
 9. The computer program product of claim 7 further comprisinginstructions for: creating at least one data cluster including, at leastin part, one or more portions of at least one of the historical projectdata and the updated historical project data.
 10. The computer programproduct of claim 7 wherein the psychometric data associated with the atleast one historical project team member is, at least in part,determined from social networking sources.
 11. The computer programproduct of claim 7 wherein the psychometric data associated with the atleast one historical project team member is, at least in part,determined through sentiment analysis.
 12. The computer program productof claim 7 further comprising instructions for: determining one or moreproject team composition recommendations, based upon, at least in part,the modified project requirements.
 13. A computer system comprising: atleast one processor; at least one memory architecture coupled with theat least one processor; a first software module executable by the atleast one processor and the at least one memory architecture, whereinthe first software module is configured to receive historical projectdata, wherein the historical project data includes at least one profileof at least one historical project team member, one or more historicalproject requirements, and one or more historical project results; asecond software module executable by the at least one processor and theat least one memory architecture, wherein the second software module isconfigured to receive psychometric data associated with the at least onehistorical project team member; a third software module executable bythe at least one processor and the at least one memory architecture,wherein the third software module is configured to generate updatedhistorical project data including, at least in part, adding psychometricdata associated with the at least one historical project team member tothe at least one profile included in the historical project data; afourth software module executable by the at least one processor and theat least one memory architecture, wherein the third software module isconfigured to receive one or more new project requirements associatedwith a new project a fifth software module executable by the at leastone processor and the at least one memory architecture, wherein thefifth software module is configured to identify a similarity between theone or more historical project requirements and the one or more newproject requirements; a sixth software module executable by the at leastone processor and the at least one memory architecture, wherein thesixth software module is configured to identify an indication of successassociated with the psychometric data included in the updated historicalproject data and with the one or more historical project requirementsidentified as similar to the one or more new project requirements; and aseventh software module executable by the at least one processor and theat least one memory architecture, wherein the seventh software module isconfigured to determine a set of modified project requirements for thenew project based upon, at least in part, identifying the indication ofsuccess.
 14. (canceled)
 15. The computer system of claim 13 furthercomprising: an eighth software module executable by the at least oneprocessor and the at least one memory architecture, wherein the eighthsoftware module is configured to create at least one data clusterincluding, at least in part, one or more portions of at least one of thehistorical project data or the updated historical project data.
 16. Thecomputer system of claim 13 wherein the psychometric data associatedwith the at least one historical project team member is, at least inpart, determined from social networking sources.
 17. The computer systemof claim 13 wherein the psychometric data associated with the at leastone historical project team member is, at least in part, determinedthrough sentiment analysis. 18-21. (canceled)
 22. A computer programproduct residing on a computer readable storage medium having aplurality of instructions stored thereon, which, when executed by aprocessor, cause the processor to perform operations comprising:identifying a similarity between one or more historical projectrequirements associated with one or more historical projects and one ormore new project requirements associated with a new project; identifyinghistorical psychometric data associated with one or more historical teammembers associated with the one or more historical projects; identifyingan indication of success associated with the historical psychometricdata and with the one or more historical project requirements identifiedas similar to the one or more new project requirements; and determiningone or more modified project requirements for the new project basedupon, at least in part, identifying the indication of success; whereinthe one or more modified project requirements for the new projectincludes, at least in part, one or more recommended team compositions,and wherein the one or more recommended team compositions includes, atleast in part, one or more recommendations associated with one or morerecommended psychometric characteristics of one or more recommended teammembers.
 23. The computer program product of claim 22 wherein theupdated historical project data includes at least one data cluster. 24.The computer program product of claim 22 wherein the psychometric dataassociated with the at least one historical project team member is, atleast in part, determined from social networking sources.
 25. Thecomputer program product of claim 22 wherein the psychometric dataassociated with the at least one historical project team member is, atleast in part, determined through sentiment analysis.